Triple
T7765641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Caldew |
E176137
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Dalston |
E557607
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dalston | Statement: [River Caldew, flowsThrough, Dalston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dalston Context triple: [River Caldew, flowsThrough, Dalston]
-
A.
Dalston
Dalston is a vibrant, rapidly gentrifying district in East London known for its nightlife, diverse community, and creative arts scene.
-
B.
Dalston
chosen
Dalston is a village in Cumbria, England, situated near Carlisle and known for its rural character and rail connections on the Cumbrian Coast Line.
-
C.
Shoreditch
Shoreditch is a vibrant East London district known for its creative industries, street art, nightlife, and tech startups.
-
D.
Stepney
Stepney is a historic district in the East End of London, England, known for its working-class roots and diverse immigrant communities.
-
E.
Islington
Islington is a vibrant inner London borough in England known for its dense urban character, cultural venues, and strong football heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69962923c8190ac74d28b4f9fe0a0 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7043279748190b30882e9cc6cca54 |
completed | March 27, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7e1a1408190a802d4f4afb8dd05 |
completed | March 29, 2026, 6:34 a.m. |
Created at: March 27, 2026, 4:09 p.m.